Articles

Human Oversight Patterns for High-Impact AI

Four practical oversight patterns — review queues, dual control, escalation trees, and time-boxed autonomy — for regulated AI programmes.

By WAIG Foundation19 Jul 2026· 7 min

Overview

High-impact AI systems need named humans in the loop. This article maps common oversight patterns used in governed deployments.

Patterns

  1. Review queue — Model proposes; reviewer approves before action
  2. Dual control — Two roles must concur on irreversible outcomes
  3. Escalation tree — Confidence or policy breach routes to a specialist
  4. Time-boxed autonomy — Limited auto-action windows with mandatory audit

How to choose

Start from residual risk, not model accuracy. Pair each pattern with evidence requirements (decision logs, source citations, refusal records).

Next steps

See related board checklist article and WAIG Academy literacy courses on /learn.

Content Attribution

Educational framing references public standards literacy. WAIG Foundation does not claim ownership of third-party standards text.